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A Tobit Ridge Regression Estimator
Department of Mathematics , King Khalid University , Saudi Arabia.
Department of Economics , Finance and Statistics, Jönköping International Business School, Jönköping University.
Department of Economics , Finance and Statistics, Jönköping International Business School, Jönköping University.
Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Department of Economics , Finance and Statistics, Jönköping International Business School, Jönköping University. (National ekonomi och Statistik/ LNUC)ORCID iD: 0000-0002-3416-5896
2014 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 43, no 1, 131-140 p.Article in journal (Refereed) Published
Abstract [en]

This article analyzes the effects of multicollienarity on the maximum likelihood (ML) estimator for the Tobit regression model. Furthermore, a ridge regression (RR) estimator is proposed since the mean squared error (MSE) of ML becomes inflated when the regressors are collinear. To investigate the performance of the traditional ML and the RR approaches we use Monte Carlo simulations where the MSE is used as performance criteria. The simulated results indicate that the RR approach should always be preferred to the ML estimation method.

Place, publisher, year, edition, pages
2014. Vol. 43, no 1, 131-140 p.
National Category
Social Sciences
Research subject
Statistics/Econometrics
Identifiers
URN: urn:nbn:se:lnu:diva-17267DOI: 10.1080/03610926.2012.655881ISI: 000327587100009OAI: oai:DiVA.org:lnu-17267DiVA: diva2:490151
Available from: 2012-02-03 Created: 2012-02-03 Last updated: 2016-12-14Bibliographically approved

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Shukur, Ghazi
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